similar to: case-cohort

I tried to compare if cch() and coxph() can generate same result for same case cohort data Use the standard data in cch(): nwtco Since in cch contains the cohort size=4028, while ccoh.data size =1154 after selection, but coxph does not contain info of cohort size=4028. The rough estimate between coxph() and cch() is same, but the lower and upper CI and P-value are a little different. Can we

Dear all, I have a couple of questions regarding the survival:::cch function. 1) I notice that Prentice and Self-Prentice functions are giving identical standard errors (not by chance but by programming design) while their estimates are different. My guess is they are both using the standard error form from Self and Prentice (1986). I see that standard errors for both methods are

----- begin included message In case cohort study, we can fit proportional hazard regression model to case-cohort data. In R, the function is cch() in Survival package Now I am working on case cohort analysis with time dependent covariates using cch() of "Survival" R package. I wonder if cch() provide this utility or not? The cch() manual does not say if time dependent covariate is

--------- begin included message --------- I tried to compare if cch() and coxph() can generate same result for same case cohort data Use the standard data in cch(): nwtco Since in cch contains the cohort size=4028, while ccoh.data size =1154 after selection, but coxph does not contain info of cohort size=4028. The rough estimate between coxph() and cch() is same, but the lower and upper CI

Case cohort function cch() is in survival package. In cch(), the prentice method is implemented like this: Prentice <- function(tenter, texit, cc, id, X, ntot,robust){ eps <- 0.00000001 cens <- as.numeric(cc>0) # Censorship indicators subcoh <- as.numeric(cc<2) # Subcohort indicators ## Calculate Prentice estimate ent2 <- tenter ent2[cc==2] <-

Hi In case cohort study, we can fit proportional hazard regression model to case-cohort data. In R, the function is cch() in Survival package Now I am working on case cohort analysis with time dependent covariates using cch() of "Survival" R package. I wonder if cch() provide this utility or not? The cch() manual does not say if time dependent covariate is allowed I know coxph() in

> Now that we have case cohort model , we have 1000 people and 50 cases > Let the first 10 cases occur at the same time > second 10 " > third 10 " > fourth 10 " > fifth 10 " > How easy is it to randomly sample 50 different > cohort controls for each group? >That

Dear all, I am reading the cch function source code. But I can not understand the following codes. Please help me. What's the fitter here? fitter <- get(method) out <- fitter(tenter = tenter, texit = texit, cc = cc, id = id, X = X, ntot = nn, robust = robust) [[alternative HTML version deleted]]

Zitat von Sébastien Le Ray <sebastien-samba at orniz.org>: >> The very strange thing is, that gpupdate tries to copy somethings >> from \\cch.intra\sysvol and not from \\dc1\sysvol... >> There a no server with name cch.intra, this is just the Realm... > > Thats expected. your.realm should resolve to all your DC in a > round-robin fashion. OK, I didn't

Rowland penny <rpenny at samba.org> schrieb: > Can you post your entire smb.conf > What OS ? > What Samba version ? Samba 4.1.6 on Ubuntu 14.04. My smb.conf: # Global parameters [global] workgroup = CCH realm = CCH.INTRA netbios name = MAIN interfaces = lo, br50 bind interfaces only = Yes server role = active directory domain

Did you try a samba-tool ntacl sysvolreset on the DC? (actually… that almost never fixed anything in my case but why not) You can also dig in the Windows events log which could give you a more detailed error Regards Le 08/04/2016 09:38, Luca Bertoncello a écrit : > Zitat von Sébastien Le Ray <sebastien-samba at orniz.org>: > >>> The very strange thing is, that gpupdate

On 11/04/16 20:50, Luca Bertoncello wrote: > Rowland penny <rpenny at samba.org> schrieb: > >> Can you post your entire smb.conf >> What OS ? >> What Samba version ? > Samba 4.1.6 on Ubuntu 14.04. > My smb.conf: > > # Global parameters > [global] > workgroup = CCH > realm = CCH.INTRA > netbios name = MAIN >

Anmeldung fehlgeschlagen: unbekannter Benutzername oder falsches Kennwort. And you did login in the domain with a domain user? Looks like it you did not. So try this from the pc which give the problem. net use x: \\cch.intra\sysvol /user:CCH\username Did it work? Ow and one i forgot.. Did you check the time on the pc and server, these must be in sync. Greetz, Louis >

Hi list! I have an Ubuntu 14.04 Server with Samba 4.1.6 acting as Active Directory controller. I worked 'till today, now I tried to join a new PC to the domain and it does not work... Problems: start and shutdown scripts are NOT called at all, logon scripts are called on the first PC, but not in the new one. The new PC did not receive the policies and did not mount the shares. gpupdate

This is correct >>that gpupdate tries to copy somethings from \\cch.intra\sysvol and not from \\dc1\sysvol... >>There a no server with name cch.intra, this is just the Realm... No not REALM, but DNSdomain but with the same name as the REALM.   You “should” be able to “ping cch.intra” or browse to \\cch.intra   if not, then your missing dns records.     If you have only

Now that we have case cohort model , we have 1000 people and 50 cases Let the first 10 cases occur at the same time second 10 " third 10 " fourth 10 " fifth 10 " How easy is it to randomly sample 50 different cohort controls for each group? That is: randomly sample 50 cohort

Hi R-experts, I want to use the jackknife function from the bootstrap package onto a linear model. I can't figure out how to do that. The manual says the following: # To jackknife functions of more complex data structures, # write theta so that its argument x # is the set of observation numbers # and simply pass as data to jackknife the vector 1,2,..n. # For example, to jackknife #

Hi All, I am in the middle of doing an analysis of a Case-Cohort design. I had three questions about the analysis: a) Does any one know of some public code for developing the patient risk sets (indexed by failure time) or is there a better way to organize the data? b) I was planning to use the Barlow weighting method. Has this or any other weighting method (Prentice, Self-Prentice) been

On 07/04/16 20:45, Luca Bertoncello wrote: > Hi list! > > I have an Ubuntu 14.04 Server with Samba 4.1.6 acting as Active Directory > controller. > > I worked 'till today, now I tried to join a new PC to the domain and it does > not work... > > Problems: start and shutdown scripts are NOT called at all, logon scripts are > called on the first PC, but not in the

Hi. I've a dataframe with about 46000 women with about 500 cases (cancers). I want to define a case-cohort sampling scheme, matching by age and hospital centre. Is there anyone who has already written a code for that? It should be something similar to the stcacoh macro in Stata. TIA, Stefano -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list